Overview

Dataset statistics

Number of variables36
Number of observations29093
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 MiB
Average record size in memory288.0 B

Variable types

CAT29
NUM7

Warnings

Systematic Name has a high cardinality: 879 distinct values High cardinality
Official Symbol has a high cardinality: 2600 distinct values High cardinality
Synonyms has a high cardinality: 2382 distinct values High cardinality
Author has a high cardinality: 9304 distinct values High cardinality
Chemical Name has a high cardinality: 5904 distinct values High cardinality
Chemical Synonyms has a high cardinality: 2586 distinct values High cardinality
Chemical Brands has a high cardinality: 1271 distinct values High cardinality
Chemical Source ID has a high cardinality: 5737 distinct values High cardinality
Molecular Formula has a high cardinality: 4910 distinct values High cardinality
ATC Codes has a high cardinality: 1427 distinct values High cardinality
CAS Number has a high cardinality: 2116 distinct values High cardinality
Related BioGRID Gene ID has a high cardinality: 207 distinct values High cardinality
Related Entrez Gene ID has a high cardinality: 207 distinct values High cardinality
Related Systematic Name has a high cardinality: 55 distinct values High cardinality
Related Official Symbol has a high cardinality: 207 distinct values High cardinality
Related Synonyms has a high cardinality: 194 distinct values High cardinality
Notes has a high cardinality: 387 distinct values High cardinality
InChIKey has a high cardinality: 5458 distinct values High cardinality
Curated By is highly correlated with Chemical SourceHigh correlation
Chemical Source is highly correlated with Curated By and 1 other fieldsHigh correlation
Method Description is highly correlated with Method and 1 other fieldsHigh correlation
Method is highly correlated with Method Description and 1 other fieldsHigh correlation
Related Organism is highly correlated with Related Organism ID and 1 other fieldsHigh correlation
Related Organism ID is highly correlated with Related Organism and 1 other fieldsHigh correlation
Related Type is highly correlated with Action and 6 other fieldsHigh correlation
Action is highly correlated with Related TypeHigh correlation
Interaction Type is highly correlated with Related TypeHigh correlation
#BioGRID Chemical Interaction ID has unique values Unique

Reproduction

Analysis started2020-11-18 22:51:13.646426
Analysis finished2020-11-18 22:51:26.583626
Duration12.94 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

#BioGRID Chemical Interaction ID
Real number (ℝ≥0)

UNIQUE

Distinct29093
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14658.87413
Minimum1
Maximum29833
Zeros0
Zeros (%)0.0%
Memory size227.3 KiB
2020-11-18T23:51:29.886963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1455.6
Q17314
median14612
Q321976
95-th percentile27864.4
Maximum29833
Range29832
Interquartile range (IQR)14662

Descriptive statistics

Standard deviation8494.8804
Coefficient of variation (CV)0.579504287
Kurtosis-1.185664303
Mean14658.87413
Median Absolute Deviation (MAD)7331
Skewness0.01478935383
Sum426470625
Variance72162993
MonotocityStrictly increasing
2020-11-18T23:51:30.015619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
197791< 0.1%
 
279111< 0.1%
 
53841< 0.1%
 
74331< 0.1%
 
12901< 0.1%
 
33391< 0.1%
 
135801< 0.1%
 
156291< 0.1%
 
94861< 0.1%
 
Other values (29083)29083> 99.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
ValueCountFrequency (%) 
298331< 0.1%
 
298321< 0.1%
 
298311< 0.1%
 
298301< 0.1%
 
298291< 0.1%
 

BioGRID Gene ID
Real number (ℝ≥0)

Distinct2612
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190842.2293
Minimum35583
Maximum4359045
Zeros0
Zeros (%)0.0%
Memory size227.3 KiB
2020-11-18T23:51:30.296081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum35583
5-th percentile106660
Q1108147
median109984
Q3112593
95-th percentile851212.6
Maximum4359045
Range4323462
Interquartile range (IQR)4446

Descriptive statistics

Standard deviation368885.2168
Coefficient of variation (CV)1.932932864
Kurtosis76.60111397
Mean190842.2293
Median Absolute Deviation (MAD)2271
Skewness7.878008067
Sum5552172976
Variance1.360763032e+11
MonotocityNot monotonic
2020-11-18T23:51:30.426174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1081473361.2%
 
1095053351.2%
 
1088282690.9%
 
1117152580.9%
 
1066632420.8%
 
1114642400.8%
 
1066582400.8%
 
1124232280.8%
 
1193602260.8%
 
1153302180.7%
 
Other values (2602)2650191.1%
 
ValueCountFrequency (%) 
355831< 0.1%
 
364346< 0.1%
 
375672< 0.1%
 
376112< 0.1%
 
381362< 0.1%
 
ValueCountFrequency (%) 
43590451< 0.1%
 
43523871< 0.1%
 
43514641< 0.1%
 
43513721< 0.1%
 
42523044< 0.1%
 

Entrez Gene ID
Real number (ℝ≥0)

Distinct2612
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98850.16341
Minimum2
Maximum13316550
Zeros0
Zeros (%)0.0%
Memory size227.3 KiB
2020-11-18T23:51:30.559944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile151
Q11813
median3784
Q36716
95-th percentile945514
Maximum13316550
Range13316548
Interquartile range (IQR)4903

Descriptive statistics

Standard deviation389075.0136
Coefficient of variation (CV)3.936007794
Kurtosis102.4079118
Mean98850.16341
Median Absolute Deviation (MAD)2552
Skewness7.67624811
Sum2875847804
Variance1.513793662e+11
MonotocityNot monotonic
2020-11-18T23:51:30.705492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
18133361.2%
 
32693351.2%
 
25542690.9%
 
57432580.9%
 
1542420.8%
 
54682400.8%
 
1482400.8%
 
65322280.8%
 
511852260.8%
 
100132180.7%
 
Other values (2602)2650191.1%
 
ValueCountFrequency (%) 
27< 0.1%
 
159< 0.1%
 
165< 0.1%
 
18420.1%
 
19150.1%
 
ValueCountFrequency (%) 
133165501< 0.1%
 
83030121< 0.1%
 
56519878< 0.1%
 
38859664< 0.1%
 
37837332< 0.1%
 

Systematic Name
Categorical

HIGH CARDINALITY

Distinct879
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
21426 
AD-006
 
226
JM21
 
218
RP11-147L20.2
 
204
RP1-130E4.1
 
204
Other values (874)
6815 
ValueCountFrequency (%) 
-2142673.6%
 
AD-0062260.8%
 
JM212180.7%
 
RP11-147L20.22040.7%
 
RP1-130E4.12040.7%
 
RP11-542K23.61970.7%
 
RP11-383C12.11180.4%
 
RP11-810O3.11130.4%
 
HIV1gp11040.4%
 
RP1-201D17__B.1980.3%
 
Other values (869)618521.3%
 
2020-11-18T23:51:30.866856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique150 ?
Unique (%)0.5%
2020-11-18T23:51:31.001878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length1
Mean length3.291960265
Min length1

Official Symbol
Categorical

HIGH CARDINALITY

Distinct2600
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
DRD2
 
336
HRH1
 
335
GABRA1
 
269
PTGS2
 
258
ADRB2
 
242
Other values (2595)
27653 
ValueCountFrequency (%) 
DRD23361.2%
 
HRH13351.2%
 
GABRA12690.9%
 
PTGS22580.9%
 
ADRB22420.8%
 
ADRA1A2400.8%
 
PPARG2400.8%
 
SLC6A42280.8%
 
CRBN2260.8%
 
HDAC62180.7%
 
Other values (2590)2650191.1%
 
2020-11-18T23:51:31.164528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique449 ?
Unique (%)1.5%
2020-11-18T23:51:31.315171image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length5
Mean length4.810126147
Min length2

Synonyms
Categorical

HIGH CARDINALITY

Distinct2382
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
2780 
D2DR|D2R
 
336
H1-R|hisH1
 
335
ECA4|EIEE19|EJM|EJM5
 
269
COX-2|COX2|GRIPGHS|PGG/HS|PGHS-2|PHS-2|hCox-2
 
258
Other values (2377)
25115 
ValueCountFrequency (%) 
-27809.6%
 
D2DR|D2R3361.2%
 
H1-R|hisH13351.2%
 
ECA4|EIEE19|EJM|EJM52690.9%
 
COX-2|COX2|GRIPGHS|PGG/HS|PGHS-2|PHS-2|hCox-22580.9%
 
ADRB2R|ADRBR|B2AR|BAR|BETA2AR2420.8%
 
CIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma2400.8%
 
ADRA1C|ADRA1L1|ALPHA1AAR2400.8%
 
5-HTT|5-HTTLPR|5HTT|HTT|OCD1|SERT|SERT1|hSERT2280.8%
 
MRT2|MRT2A2260.8%
 
Other values (2372)2393982.3%
 
2020-11-18T23:51:31.467514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique419 ?
Unique (%)1.4%
2020-11-18T23:51:31.628379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length202
Median length18
Mean length21.18997697
Min length1

Organism ID
Real number (ℝ≥0)

Distinct21
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40178.96532
Minimum6239
Maximum559292
Zeros0
Zeros (%)0.0%
Memory size227.3 KiB
2020-11-18T23:51:31.758598image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum6239
5-th percentile9606
Q19606
median9606
Q39606
95-th percentile511145
Maximum559292
Range553053
Interquartile range (IQR)0

Descriptive statistics

Standard deviation116246.8037
Coefficient of variation (CV)2.893225417
Kurtosis11.91874677
Mean40178.96532
Median Absolute Deviation (MAD)0
Skewness3.693549268
Sum1168926638
Variance1.351331937e+10
MonotocityNot monotonic
2020-11-18T23:51:31.854511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
96062684192.3%
 
51114515905.5%
 
2243081640.6%
 
2375611080.4%
 
116761050.4%
 
171101820.3%
 
10298650.2%
 
170187610.2%
 
10245210.1%
 
1037610< 0.1%
 
Other values (11)460.2%
 
ValueCountFrequency (%) 
62398< 0.1%
 
96062684192.3%
 
100902< 0.1%
 
101162< 0.1%
 
10245210.1%
 
ValueCountFrequency (%) 
5592927< 0.1%
 
51114515905.5%
 
3475158< 0.1%
 
2726342< 0.1%
 
2690844< 0.1%
 

Organism
Categorical

Distinct18
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
Homo sapiens
26841 
Escherichia coli
 
1595
Bacillus subtilis
 
164
Streptococcus pneumoniae
 
143
Candida albicans
 
108
Other values (13)
 
242
ValueCountFrequency (%) 
Homo sapiens2684192.3%
 
Escherichia coli15955.5%
 
Bacillus subtilis1640.6%
 
Streptococcus pneumoniae1430.5%
 
Candida albicans1080.4%
 
Human Immunodeficiency Virus 11050.4%
 
Human Herpesvirus 1650.2%
 
Vaccinia Virus210.1%
 
Human Herpesvirus 410< 0.1%
 
Leishmania major8< 0.1%
 
Other values (8)330.1%
 
2020-11-18T23:51:31.984158image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T23:51:32.111076image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length12
Mean length12.41814182
Min length12

Action
Categorical

HIGH CORRELATION

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
unknown
12914 
inhibitor
5353 
antagonist
3954 
agonist
3116 
potentiator
 
870
Other values (30)
2886 
ValueCountFrequency (%) 
unknown1291444.4%
 
inhibitor535318.4%
 
antagonist395413.6%
 
agonist311610.7%
 
potentiator8703.0%
 
binder4111.4%
 
cofactor3911.3%
 
degradation3691.3%
 
positive allosteric modulator2891.0%
 
inducer2090.7%
 
Other values (25)12174.2%
 
2020-11-18T23:51:32.247461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2020-11-18T23:51:32.514938image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length31
Median length7
Mean length8.381535077
Min length6

Interaction Type
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
target
28724 
recruited e3 ligase
 
199
recruited E3 ligase
 
167
lysosome-targeting protein
 
2
autophagy-targeting protein
 
1
ValueCountFrequency (%) 
target2872498.7%
 
recruited e3 ligase1990.7%
 
recruited E3 ligase1670.6%
 
lysosome-targeting protein2< 0.1%
 
autophagy-targeting protein1< 0.1%
 
2020-11-18T23:51:32.644640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-18T23:51:32.728417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:32.852128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length27
Median length6
Mean length6.16564122
Min length6

Author
Categorical

HIGH CARDINALITY

Distinct9304
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
Berman HM (2000)
3966 
Imming P (2006)
3480 
Overington JP (2006)
3455 
Chen X (2002)
 
1032
Riss J (2008)
 
251
Other values (9299)
16909 
ValueCountFrequency (%) 
Berman HM (2000)396613.6%
 
Imming P (2006)348012.0%
 
Overington JP (2006)345511.9%
 
Chen X (2002)10323.5%
 
Riss J (2008)2510.9%
 
Moehler H (2002)1830.6%
 
Yamakura T (2001)1650.6%
 
Mehta AK (1999)1100.4%
 
Nasrallah HA (2008)1090.4%
 
Kvernmo T (2008)1000.3%
 
Other values (9294)1624255.8%
 
2020-11-18T23:51:33.003501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6696 ?
Unique (%)23.0%
2020-11-18T23:51:33.158432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length36
Median length16
Mean length16.32097068
Min length11

Pubmed ID
Real number (ℝ≥0)

Distinct9532
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14267905.68
Minimum10722
Maximum32840532
Zeros0
Zeros (%)0.0%
Memory size227.3 KiB
2020-11-18T23:51:33.298871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10722
5-th percentile4402328.8
Q110592235
median15939622
Q317139284
95-th percentile20810709.4
Maximum32840532
Range32829810
Interquartile range (IQR)6547049

Descriptive statistics

Standard deviation5080699.196
Coefficient of variation (CV)0.35609285
Kurtosis1.014743907
Mean14267905.68
Median Absolute Deviation (MAD)3497863
Skewness-0.04868991935
Sum4.150961799e+11
Variance2.581350432e+13
MonotocityNot monotonic
2020-11-18T23:51:33.505798image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
10592235396613.6%
 
17016423348012.0%
 
17139284345511.9%
 
1175235210323.5%
 
183844562510.9%
 
117520901830.6%
 
112644491640.6%
 
102092321100.4%
 
178489191090.4%
 
186911321000.3%
 
Other values (9522)1624355.8%
 
ValueCountFrequency (%) 
107229< 0.1%
 
111341< 0.1%
 
167162< 0.1%
 
173741< 0.1%
 
185652< 0.1%
 
ValueCountFrequency (%) 
328405321< 0.1%
 
328039781< 0.1%
 
327788451< 0.1%
 
327505661< 0.1%
 
327282162< 0.1%
 

BioGRID Publication ID
Real number (ℝ≥0)

Distinct9532
Distinct (%)32.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176055.8821
Minimum283
Maximum224925
Zeros0
Zeros (%)0.0%
Memory size227.3 KiB
2020-11-18T23:51:33.677924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum283
5-th percentile171741
Q1171742
median173938
Q3178445
95-th percentile188559.4
Maximum224925
Range224642
Interquartile range (IQR)6703

Descriptive statistics

Standard deviation14019.82986
Coefficient of variation (CV)0.07963283983
Kurtosis50.17064479
Mean176055.8821
Median Absolute Deviation (MAD)2197
Skewness-3.403223845
Sum5121993777
Variance196555629.2
MonotocityNot monotonic
2020-11-18T23:51:33.853508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
172122396613.6%
 
171742348012.0%
 
171741345511.9%
 
17174010323.5%
 
1742022510.9%
 
1745371830.6%
 
1745681640.6%
 
1745691100.4%
 
1746161090.4%
 
1746621000.3%
 
Other values (9522)1624355.8%
 
ValueCountFrequency (%) 
2831< 0.1%
 
4471< 0.1%
 
7441< 0.1%
 
10392< 0.1%
 
10422< 0.1%
 
ValueCountFrequency (%) 
2249251< 0.1%
 
2249241< 0.1%
 
2249232< 0.1%
 
2249222< 0.1%
 
2249212< 0.1%
 

BioGRID Chemical ID
Real number (ℝ≥0)

Distinct5904
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2239.205479
Minimum1
Maximum9750
Zeros0
Zeros (%)0.0%
Memory size227.3 KiB
2020-11-18T23:51:34.020066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile109
Q1455
median1142
Q33362
95-th percentile7819
Maximum9750
Range9749
Interquartile range (IQR)2907

Descriptive statistics

Standard deviation2474.590449
Coefficient of variation (CV)1.105119861
Kurtosis0.8621257859
Mean2239.205479
Median Absolute Deviation (MAD)933
Skewness1.374466314
Sum65145205
Variance6123597.889
MonotocityNot monotonic
2020-11-18T23:51:34.177261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1514131.4%
 
1092340.8%
 
1362110.7%
 
8992040.7%
 
1371420.5%
 
10381290.4%
 
6641120.4%
 
3261010.3%
 
888970.3%
 
139960.3%
 
Other values (5894)2735494.0%
 
ValueCountFrequency (%) 
16< 0.1%
 
2280.1%
 
4150.1%
 
5360.1%
 
66< 0.1%
 
ValueCountFrequency (%) 
97501< 0.1%
 
97491< 0.1%
 
97481< 0.1%
 
97471< 0.1%
 
97461< 0.1%
 

Chemical Name
Categorical

HIGH CARDINALITY

Distinct5904
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
NADH
 
413
Pyridoxal Phosphate
 
234
L-Glutamic Acid
 
211
Zonisamide
 
204
Glutathione
 
142
Other values (5899)
27889 
ValueCountFrequency (%) 
NADH4131.4%
 
Pyridoxal Phosphate2340.8%
 
L-Glutamic Acid2110.7%
 
Zonisamide2040.7%
 
Glutathione1420.5%
 
Ergoloid mesylate1290.4%
 
Galantamine1120.4%
 
Olanzapine1010.3%
 
Ethanol970.3%
 
Glycine960.3%
 
Other values (5894)2735494.0%
 
2020-11-18T23:51:34.335793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2503 ?
Unique (%)8.6%
2020-11-18T23:51:34.503424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length874
Median length12
Mean length22.17474994
Min length3

Chemical Synonyms
Categorical

HIGH CARDINALITY

Distinct2586
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
8236 
DPNH|Reduced nicotinamide adenine diphosphate|Nicotinamide-adenine dinucleotide, reduced|1,4-dihydronicotinamide adenine dinucleotide|Reduced nicotinamide-adenine dinucleotide|NAD reduced form|Nicotinamide adenine dinucleotide (reduced)
 
413
Pyridoxal 5-monophosphoric acid ester|PLP|Pyridoxal phosphate anhydrous|3-hydroxy-2-methyl-5-((phosphonooxy)methyl)-4-pyridinecarboxaldehyde|Pyridoxal 5-phosphate|Pyridoxal-P|Pyridoxal 5'-phosphate|Pyridoxal P|Codecarboxylase|Pyridoxal-5P|3-hydroxy-5-(hydroxymethyl)-2-methylisonicotinaldehyde 5-phosphate
 
234
(S)-Glutamic acid|(2S)-2-Aminopentanedioic acid|L-Glutamate|Glutamic acid|(S)-2-Aminopentanedioic acid|L-Glutaminic acid|Glu
 
211
1,2-Benzisoxazole-3-methanesulfonamide|Zonisamida|Zonisamidum|Benzo[D]isoxazol-3-yl-methanesulfonamide|3-(Sulfamoylmethyl)-1,2-benzisoxazole
 
204
Other values (2581)
19795 
ValueCountFrequency (%) 
-823628.3%
 
DPNH|Reduced nicotinamide adenine diphosphate|Nicotinamide-adenine dinucleotide, reduced|1,4-dihydronicotinamide adenine dinucleotide|Reduced nicotinamide-adenine dinucleotide|NAD reduced form|Nicotinamide adenine dinucleotide (reduced)4131.4%
 
Pyridoxal 5-monophosphoric acid ester|PLP|Pyridoxal phosphate anhydrous|3-hydroxy-2-methyl-5-((phosphonooxy)methyl)-4-pyridinecarboxaldehyde|Pyridoxal 5-phosphate|Pyridoxal-P|Pyridoxal 5'-phosphate|Pyridoxal P|Codecarboxylase|Pyridoxal-5P|3-hydroxy-5-(hydroxymethyl)-2-methylisonicotinaldehyde 5-phosphate2340.8%
 
(S)-Glutamic acid|(2S)-2-Aminopentanedioic acid|L-Glutamate|Glutamic acid|(S)-2-Aminopentanedioic acid|L-Glutaminic acid|Glu2110.7%
 
1,2-Benzisoxazole-3-methanesulfonamide|Zonisamida|Zonisamidum|Benzo[D]isoxazol-3-yl-methanesulfonamide|3-(Sulfamoylmethyl)-1,2-benzisoxazole2040.7%
 
Glutathione-SH|Glutathione|5-L-Glutamyl-L-cysteinylglycine|N-(N-gamma-L-Glutamyl-L-cysteinyl)glycine|gamma-L-Glutamyl-L-cysteinyl-glycine|Reduced glutathione|GSH1420.5%
 
Dihydroergotoxine Methanesulfonate|codergocrine mesylate|dihydroergotoxine monomethanesulfonate|Dihydroergotoxine Mesylate|co-dergocrine mesilate|dihydroergotoxine methanesulfonate|co-dergocrine mesylate|ergoloid methanesulfonate|Ergoloid Mesylates|co-dergocrine methanesulfonate|ergoloid methanesulfonates|Dihydroergotoxine Mesilate|codergocrine methanesulfonate|codergocrine mesilate|dihydrogenated ergot alkaloids|dihydroergotoxine methanesulfonates|hydrogenated ergot alkaloids1290.4%
 
Galanthamine|(-)-Galanthamine1120.4%
 
Olanzapinum|2-methyl-4-(4-methyl-1-piperazinyl)-10H-thieno[2,3-b][1,5]benzodiazepine|Olanzapin|Olanzapine|Zyprexa|Olanzapina1010.3%
 
thanol|Methylcarbinol|Ethyl Alcohol|Alcohol|Alcohol etlico|thylalkohol|Grain alcohol|Alcohol (ethyl)|1-Hydroxyethane|Alcohol anhydrous|thanol|Alcohol, denatured|etanol|Dehydrated ethanol|Spiritus vini|Hydroxyethane|Alkohol|Alcool thylique|Alcohol denatured970.3%
 
Other values (2576)1921466.0%
 
2020-11-18T23:51:34.666395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique889 ?
Unique (%)3.1%
2020-11-18T23:51:35.043572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3645
Median length77
Mean length134.6815041
Min length1

Chemical Brands
Categorical

HIGH CARDINALITY

Distinct1271
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
13620 
primene 10%|aminosyn ii 5% inj
 
283
freamine iii|primene 10%|2.5%
 
211
zonegran|zonisamide
 
204
2.5% travasol amino acid injec
 
159
Other values (1266)
14616 
ValueCountFrequency (%) 
-1362046.8%
 
primene 10%|aminosyn ii 5% inj2831.0%
 
freamine iii|primene 10%|2.5% 2110.7%
 
zonegran|zonisamide2040.7%
 
2.5% travasol amino acid injec1590.5%
 
amo endosol extra|bss plus|nav1420.5%
 
hydergine tablets, 1mg1290.4%
 
reminyl -(12mg)|pms-galantam1120.4%
 
olanzapine and fluoxetine|sand1010.3%
 
lisa frank bubblegum antisepti970.3%
 
Other values (1261)1403548.2%
 
2020-11-18T23:51:35.260140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique112 ?
Unique (%)0.4%
2020-11-18T23:51:35.464222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length30
Median length7
Mean length14.30072526
Min length1

Chemical Source
Categorical

HIGH CORRELATION

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
DRUGBANK
27904 
PUBCHEM
 
575
BIOGRID
 
369
CHEMSPIDER
 
206
CHEMBL
 
36
Other values (2)
 
3
ValueCountFrequency (%) 
DRUGBANK2790495.9%
 
PUBCHEM5752.0%
 
BIOGRID3691.3%
 
CHEMSPIDER2060.7%
 
CHEMBL360.1%
 
CHEBI2< 0.1%
 
PDB1< 0.1%
 
2020-11-18T23:51:35.623099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-18T23:51:35.723172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:35.914872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length8
Mean length7.978860894
Min length3

Chemical Source ID
Categorical

HIGH CARDINALITY

Distinct5737
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
DB00157
 
413
-
 
369
DB00114
 
234
DB00142
 
211
DB00909
 
204
Other values (5732)
27662 
ValueCountFrequency (%) 
DB001574131.4%
 
-3691.3%
 
DB001142340.8%
 
DB001422110.7%
 
DB009092040.7%
 
DB001431420.5%
 
DB010491290.4%
 
DB006741120.4%
 
DB003341010.3%
 
DB00898970.3%
 
Other values (5727)2708193.1%
 
2020-11-18T23:51:36.099162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2375 ?
Unique (%)8.2%
2020-11-18T23:51:36.278068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length7
Mean length6.956450005
Min length1

Molecular Formula
Categorical

HIGH CARDINALITY

Distinct4910
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
 
846
C21H29N7O14P2
 
413
C8H10NO6P
 
234
C5H9NO4
 
216
C8H8N2O3S
 
205
Other values (4905)
27179 
ValueCountFrequency (%) 
-8462.9%
 
C21H29N7O14P24131.4%
 
C8H10NO6P2340.8%
 
C5H9NO42160.7%
 
C8H8N2O3S2050.7%
 
C17H21NO31460.5%
 
C10H17N3O6S1420.5%
 
C30H41N5O8S1290.4%
 
C17H20N4S1010.3%
 
C2H5NO21000.3%
 
Other values (4900)2656191.3%
 
2020-11-18T23:51:36.443203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1867 ?
Unique (%)6.4%
2020-11-18T23:51:36.606379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length149
Median length10
Mean length9.997972021
Min length1

Chemical Type
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
small molecule
27480 
biologic
 
1596
polypeptidic
 
17
ValueCountFrequency (%) 
small molecule2748094.5%
 
biologic15965.5%
 
polypeptidic170.1%
 
2020-11-18T23:51:36.791073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T23:51:36.901010image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:37.043930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length14
Mean length13.66967999
Min length8

ATC Codes
Categorical

HIGH CARDINALITY

Distinct1427
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
12905 
A11HA06
 
234
N03AX15
 
204
V03AB32
 
142
C04AE51|C04AE01
 
129
Other values (1422)
15479 
ValueCountFrequency (%) 
-1290544.4%
 
A11HA062340.8%
 
N03AX152040.7%
 
V03AB321420.5%
 
C04AE51|C04AE011290.4%
 
N06DA041120.4%
 
N05AH031010.3%
 
D08AX08|V03AB16|V03AZ01970.3%
 
B05CX03960.3%
 
N06BC01|V04CG30750.3%
 
Other values (1417)1499851.6%
 
2020-11-18T23:51:37.245137image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique134 ?
Unique (%)0.5%
2020-11-18T23:51:37.433209image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length303
Median length7
Mean length7.548104355
Min length1

CAS Number
Categorical

HIGH CARDINALITY

Distinct2116
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
7655 
58-68-4
 
413
54-47-7
 
234
56-86-0
 
211
68291-97-4
 
204
Other values (2111)
20376 
ValueCountFrequency (%) 
-765526.3%
 
58-68-44131.4%
 
54-47-72340.8%
 
56-86-02110.7%
 
68291-97-42040.7%
 
70-18-81420.5%
 
8067-24-11290.4%
 
357-70-01120.4%
 
132539-06-11010.3%
 
64-17-5970.3%
 
Other values (2106)1979568.0%
 
2020-11-18T23:51:37.627516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique244 ?
Unique (%)0.8%
2020-11-18T23:51:37.841378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length8
Mean length6.882205341
Min length1

Curated By
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
DRUGBANK
27785 
BINDINGDB
 
714
BIOGRID
 
594
ValueCountFrequency (%) 
DRUGBANK2778595.5%
 
BINDINGDB7142.5%
 
BIOGRID5942.0%
 
2020-11-18T23:51:38.108708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T23:51:38.196624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:38.311844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length8
Mean length8.004124704
Min length7

Method
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
PROTAC
 
321
Molecular Glue
 
18
HaloPROTAC
 
15
SNIPER
 
9
Other values (3)
 
6
ValueCountFrequency (%) 
-2872498.7%
 
PROTAC3211.1%
 
Molecular Glue180.1%
 
HaloPROTAC150.1%
 
SNIPER9< 0.1%
 
CLIPTAC3< 0.1%
 
LYTAC2< 0.1%
 
ATTEC1< 0.1%
 
2020-11-18T23:51:38.670091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-18T23:51:38.897822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:39.312303image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length1
Mean length1.070429313
Min length1

Method Description
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
Proteolysis Targeting Chimera; structured as E3 binding moiety--linker--target binding moiety; target degraded via UPS
 
321
Single chemical moiety that contacts both the E3 and the target in a ternary complex; structured as a single chemical entity without linkers; target degraded via UPS or otherwise inactivated in the ternary complex
 
18
PROTAC variant that induces degradation of HaloTag fusion proteins; structured as E3 binding moiety--linker--HaloTag binding moiety; target degraded via UPS
 
15
Specific and Non-genetic Inhibitor-of-apoptosis proteins (IAPs)-dependent Protein Eraser; structured as IAP ligand--linker--target binding moiety; target degraded via UPS
 
9
Other values (3)
 
6
ValueCountFrequency (%) 
-2872498.7%
 
Proteolysis Targeting Chimera; structured as E3 binding moiety--linker--target binding moiety; target degraded via UPS3211.1%
 
Single chemical moiety that contacts both the E3 and the target in a ternary complex; structured as a single chemical entity without linkers; target degraded via UPS or otherwise inactivated in the ternary complex180.1%
 
PROTAC variant that induces degradation of HaloTag fusion proteins; structured as E3 binding moiety--linker--HaloTag binding moiety; target degraded via UPS150.1%
 
Specific and Non-genetic Inhibitor-of-apoptosis proteins (IAPs)-dependent Protein Eraser; structured as IAP ligand--linker--target binding moiety; target degraded via UPS9< 0.1%
 
PROTAC variant formed in cells by click chemistry; structured as E3 binding moiety--linker--target binding moiety; target degraded via UPS3< 0.1%
 
Lysosome Targeting Chimera; structured as glycopeptide ligand--linker--target binding moiety; target degraded via endosome-lysosome system2< 0.1%
 
Autophagosome Tethering Compound; structured as a LC3 binding moiety--linker--target binding moiety; target degraded via autophagic degradation1< 0.1%
 
2020-11-18T23:51:39.635006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-18T23:51:39.859222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:40.524923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length213
Median length1
Mean length2.582717492
Min length1

Related BioGRID Gene ID
Categorical

HIGH CARDINALITY

Distinct207
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
117036
 
26
106543
 
12
107160
 
11
108403
 
10
Other values (202)
 
310
ValueCountFrequency (%) 
-2872498.7%
 
117036260.1%
 
10654312< 0.1%
 
10716011< 0.1%
 
10840310< 0.1%
 
1074569< 0.1%
 
1077738< 0.1%
 
1068627< 0.1%
 
1074547< 0.1%
 
1119735< 0.1%
 
Other values (197)2740.9%
 
2020-11-18T23:51:40.887140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique150 ?
Unique (%)0.5%
2020-11-18T23:51:41.255973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length1
Mean length1.063451689
Min length1

Related Entrez Gene ID
Categorical

HIGH CARDINALITY

Distinct207
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
23476
 
26
25
 
12
695
 
11
2099
 
10
Other values (202)
 
310
ValueCountFrequency (%) 
-2872498.7%
 
23476260.1%
 
2512< 0.1%
 
69511< 0.1%
 
209910< 0.1%
 
10219< 0.1%
 
13828< 0.1%
 
3677< 0.1%
 
10197< 0.1%
 
80195< 0.1%
 
Other values (197)2740.9%
 
2020-11-18T23:51:41.649025image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique150 ?
Unique (%)0.5%
2020-11-18T23:51:42.040021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length1
Mean length1.04062833
Min length1

Related Systematic Name
Categorical

HIGH CARDINALITY

Distinct55
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28962 
RP11-83J21.1
 
12
RP1-164F3.2
 
11
RP1-130E4.1
 
10
RP11-66D17.4
 
8
Other values (50)
 
90
ValueCountFrequency (%) 
-2896299.5%
 
RP11-83J21.112< 0.1%
 
RP1-164F3.211< 0.1%
 
RP1-130E4.110< 0.1%
 
RP11-66D17.48< 0.1%
 
RP11-383C12.17< 0.1%
 
RP11-94L15.25< 0.1%
 
RP11-374P20.35< 0.1%
 
tcag7.11785< 0.1%
 
DADB-17J1.35< 0.1%
 
Other values (45)630.2%
 
2020-11-18T23:51:42.426548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique35 ?
Unique (%)0.1%
2020-11-18T23:51:42.770218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length23
Median length1
Mean length1.046712268
Min length1

Related Official Symbol
Categorical

HIGH CARDINALITY

Distinct207
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
BRD4
 
26
ABL1
 
12
BTK
 
11
ESR1
 
10
Other values (202)
 
310
ValueCountFrequency (%) 
-2872498.7%
 
BRD4260.1%
 
ABL112< 0.1%
 
BTK11< 0.1%
 
ESR110< 0.1%
 
CDK69< 0.1%
 
CRABP28< 0.1%
 
AR7< 0.1%
 
CDK47< 0.1%
 
IKZF15< 0.1%
 
Other values (197)2740.9%
 
2020-11-18T23:51:43.141164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique150 ?
Unique (%)0.5%
2020-11-18T23:51:43.528199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length1
Mean length1.046402915
Min length1

Related Synonyms
Categorical

HIGH CARDINALITY

Distinct194
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28740 
CAP|HUNK1|HUNKI|MCAP
 
26
ABL|JTK7|bcr/abl|c-ABL|c-ABL1|p150|v-abl
 
12
AGMX1|AT|ATK|BPK|IMD1|PSCTK1|XLA
 
11
ER|ESR|ESRA|ESTRR|Era|NR3A1
 
10
Other values (189)
 
294
ValueCountFrequency (%) 
-2874098.8%
 
CAP|HUNK1|HUNKI|MCAP260.1%
 
ABL|JTK7|bcr/abl|c-ABL|c-ABL1|p150|v-abl12< 0.1%
 
AGMX1|AT|ATK|BPK|IMD1|PSCTK1|XLA11< 0.1%
 
ER|ESR|ESRA|ESTRR|Era|NR3A110< 0.1%
 
MCPH12|PLSTIRE9< 0.1%
 
CRABP-II|RBP68< 0.1%
 
AIS|DHTR|HUMARA|HYSP1|KD|NR3C4|SBMA|SMAX1|TFM7< 0.1%
 
CMM3|PSK-J37< 0.1%
 
ORFX|RING3L5< 0.1%
 
Other values (184)2580.9%
 
2020-11-18T23:51:43.921250image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique139 ?
Unique (%)0.5%
2020-11-18T23:51:44.360742image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length76
Median length1
Mean length1.288557385
Min length1

Related Organism ID
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
9606
 
366
10090
 
2
11103
 
1
ValueCountFrequency (%) 
-2872498.7%
 
96063661.3%
 
100902< 0.1%
 
111031< 0.1%
 
2020-11-18T23:51:44.897046image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-18T23:51:45.041890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:45.294482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length1
Mean length1.038153508
Min length1

Related Organism
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
Homo sapiens
 
366
Mus musculus
 
2
Hepatitus C Virus
 
1
ValueCountFrequency (%) 
-2872498.7%
 
Homo sapiens3661.3%
 
Mus musculus2< 0.1%
 
Hepatitus C Virus1< 0.1%
 
2020-11-18T23:51:45.611959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-18T23:51:45.826089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:46.117902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length1
Mean length1.13968996
Min length1

Related Type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28724 
target
 
369
ValueCountFrequency (%) 
-2872498.7%
 
target3691.3%
 
2020-11-18T23:51:46.411944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-18T23:51:46.614119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:46.827083image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length1
Mean length1.063417317
Min length1

Notes
Categorical

HIGH CARDINALITY

Distinct387
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
28700 
Standardized BVL Name: SNIPER(CRABP)-11(IAP pan-ligand:MV1 --- CRABP-II:ATRA)
 
3
Standardized BVL Name: ARV-825(CRBN:pomalidomide --- BRD4:OTX015)
 
2
Positive hit in high screen assay validated by IC-50 determination.
 
2
Standardized BVL Name: compound MZ1(VHL:VHL-1 --- BRD4:JQ1)
 
2
Other values (382)
 
384
ValueCountFrequency (%) 
-2870098.6%
 
Standardized BVL Name: SNIPER(CRABP)-11(IAP pan-ligand:MV1 --- CRABP-II:ATRA)3< 0.1%
 
Standardized BVL Name: ARV-825(CRBN:pomalidomide --- BRD4:OTX015)2< 0.1%
 
Positive hit in high screen assay validated by IC-50 determination.2< 0.1%
 
Standardized BVL Name: compound MZ1(VHL:VHL-1 --- BRD4:JQ1)2< 0.1%
 
Standardized BVL Name: dBET1(CRBN:thalidomide --- BRD4:JQ1)2< 0.1%
 
PpIX ablates TAp73/MDM2, TAp73/MDMX and TAp73/Itch complexes2< 0.1%
 
Standardized BVL Name: XZ9002 (VHL:VH032 --- HDAC3:SR-3558)1< 0.1%
 
Standardized BVL Name: PROTAC2(CRBN:CRBN ligand --- MT1HL1:foretinib)1< 0.1%
 
Standardized BVL Name: BSJ03204 (CRBN:thalidomide --- CDK4:palbociclib)1< 0.1%
 
Other values (377)3771.3%
 
2020-11-18T23:51:47.194370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique380 ?
Unique (%)1.3%
2020-11-18T23:51:47.628355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length183
Median length1
Mean length1.987213419
Min length1

InChIKey
Categorical

HIGH CARDINALITY

Distinct5458
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size227.3 KiB
-
 
2351
BOPGDPNILDQYTO-NNYOXOHSSA-N
 
413
NGVDGCNFYWLIFO-UHFFFAOYSA-N
 
234
WHUUTDBJXJRKMK-VKHMYHEASA-N
 
211
UBQNRHZMVUUOMG-UHFFFAOYSA-N
 
204
Other values (5453)
25680 
ValueCountFrequency (%) 
-23518.1%
 
BOPGDPNILDQYTO-NNYOXOHSSA-N4131.4%
 
NGVDGCNFYWLIFO-UHFFFAOYSA-N2340.8%
 
WHUUTDBJXJRKMK-VKHMYHEASA-N2110.7%
 
UBQNRHZMVUUOMG-UHFFFAOYSA-N2040.7%
 
RWSXRVCMGQZWBV-WDSKDSINSA-N1420.5%
 
FQHMMOGHDWAXDI-WUQHHHCFSA-N1290.4%
 
ASUTZQLVASHGKV-JDFRZJQESA-N1120.4%
 
KVWDHTXUZHCGIO-UHFFFAOYSA-N1010.3%
 
LFQSCWFLJHTTHZ-UHFFFAOYSA-N970.3%
 
Other values (5448)2509986.3%
 
2020-11-18T23:51:48.144095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2312 ?
Unique (%)7.9%
2020-11-18T23:51:48.481174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length36
Median length27
Mean length24.91070017
Min length1

Interactions

2020-11-18T23:51:17.282163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:17.424431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:17.686164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:17.831800image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:17.966419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:18.104007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:18.247403image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:18.381072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:18.511190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:18.631982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:18.762832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:18.889138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.021212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.145024image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.271839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.417644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.555376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.696440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.831351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:19.971906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:20.105439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:20.239924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:20.372326image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:20.495656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:20.628426image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:20.754134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:20.884863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:21.007678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:21.134361image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:21.274293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:21.406471image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:21.670863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:21.810530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:21.950135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.080861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.215516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.342194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.460872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.589501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.712640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.842336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:22.962049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:23.086979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:23.219614image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:23.342353image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:23.474519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:23.605376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:23.750384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:23.885571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-18T23:51:48.742306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-18T23:51:49.235956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-18T23:51:49.717473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-18T23:51:50.270590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-18T23:51:51.040139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-18T23:51:24.287900image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-18T23:51:26.132629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

#BioGRID Chemical Interaction IDBioGRID Gene IDEntrez Gene IDSystematic NameOfficial SymbolSynonymsOrganism IDOrganismActionInteraction TypeAuthorPubmed IDBioGRID Publication IDBioGRID Chemical IDChemical NameChemical SynonymsChemical BrandsChemical SourceChemical Source IDMolecular FormulaChemical TypeATC CodesCAS NumberCurated ByMethodMethod DescriptionRelated BioGRID Gene IDRelated Entrez Gene IDRelated Systematic NameRelated Official SymbolRelated SynonymsRelated Organism IDRelated OrganismRelated TypeNotesInChIKey
011084472147-F2PT|RPRGL2|THPH19606Homo sapiensinhibitortargetEriksson BI (2000)110558891717391LepirudinLepirudin recombinant|Hirudin variant-1refludanDRUGBANKDB00001C287H440N80O110S6biologicB01AE02138068-37-8DRUGBANK------------
121084472147-F2PT|RPRGL2|THPH19606Homo sapiensinhibitortargetWarkentin TE (2000)109126441717381LepirudinLepirudin recombinant|Hirudin variant-1refludanDRUGBANKDB00001C287H440N80O110S6biologicB01AE02138068-37-8DRUGBANK------------
231084472147-F2PT|RPRGL2|THPH19606Homo sapiensinhibitortargetSzaba FM (2002)118070121717371LepirudinLepirudin recombinant|Hirudin variant-1refludanDRUGBANKDB00001C287H440N80O110S6biologicB01AE02138068-37-8DRUGBANK------------
341084472147-F2PT|RPRGL2|THPH19606Homo sapiensinhibitortargetFabrizio MC (2001)114674391717361LepirudinLepirudin recombinant|Hirudin variant-1refludanDRUGBANKDB00001C287H440N80O110S6biologicB01AE02138068-37-8DRUGBANK------------
451084472147-F2PT|RPRGL2|THPH19606Homo sapiensinhibitortargetTurpie AG (1999)105055361717351LepirudinLepirudin recombinant|Hirudin variant-1refludanDRUGBANKDB00001C287H440N80O110S6biologicB01AE02138068-37-8DRUGBANK------------
561084472147-F2PT|RPRGL2|THPH19606Homo sapiensinhibitortargetChen X (2002)117523521717401LepirudinLepirudin recombinant|Hirudin variant-1refludanDRUGBANKDB00001C287H440N80O110S6biologicB01AE02138068-37-8DRUGBANK------------
671085072213RP11-474I16.2FCGR2BCD32|CD32B|FCG2|FCGR2|IGFR29606Homo sapiensunknowntargetImming P (2006)170164231717422CetuximabImmunoglobulin G 1 (human-mouse monoclonal C 225 gamma 1 - chain anti-human epidermal growt factor receptor), disulfide wit human-mouse monoclonal C 225 kappa - chain, dimer|Ctuximab|Cetuximab|CetuximabumerbituxDRUGBANKDB00002C6484H10042N1732O2023S36biologicL01XC06205923-56-4DRUGBANK------------
781085072213RP11-474I16.2FCGR2BCD32|CD32B|FCG2|FCGR2|IGFR29606Homo sapiensunknowntargetOverington JP (2006)171392841717412CetuximabImmunoglobulin G 1 (human-mouse monoclonal C 225 gamma 1 - chain anti-human epidermal growt factor receptor), disulfide wit human-mouse monoclonal C 225 kappa - chain, dimer|Ctuximab|Cetuximab|CetuximabumerbituxDRUGBANKDB00002C6484H10042N1732O2023S36biologicL01XC06205923-56-4DRUGBANK------------
89107177716-C1S-9606Homo sapiensunknowntargetImming P (2006)170164231717422CetuximabImmunoglobulin G 1 (human-mouse monoclonal C 225 gamma 1 - chain anti-human epidermal growt factor receptor), disulfide wit human-mouse monoclonal C 225 kappa - chain, dimer|Ctuximab|Cetuximab|CetuximabumerbituxDRUGBANKDB00002C6484H10042N1732O2023S36biologicL01XC06205923-56-4DRUGBANK------------
910107177716-C1S-9606Homo sapiensunknowntargetOverington JP (2006)171392841717412CetuximabImmunoglobulin G 1 (human-mouse monoclonal C 225 gamma 1 - chain anti-human epidermal growt factor receptor), disulfide wit human-mouse monoclonal C 225 kappa - chain, dimer|Ctuximab|Cetuximab|CetuximabumerbituxDRUGBANKDB00002C6484H10042N1732O2023S36biologicL01XC06205923-56-4DRUGBANK------------

Last rows

#BioGRID Chemical Interaction IDBioGRID Gene IDEntrez Gene IDSystematic NameOfficial SymbolSynonymsOrganism IDOrganismActionInteraction TypeAuthorPubmed IDBioGRID Publication IDBioGRID Chemical IDChemical NameChemical SynonymsChemical BrandsChemical SourceChemical Source IDMolecular FormulaChemical TypeATC CodesCAS NumberCurated ByMethodMethod DescriptionRelated BioGRID Gene IDRelated Entrez Gene IDRelated Systematic NameRelated Official SymbolRelated SynonymsRelated Organism IDRelated OrganismRelated TypeNotesInChIKey
29083298241114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetDesai RC (2003)128735172249209745(5S)-5-[3-[3-(4-Phenoxyphenoxy)propoxy]phenyl]-1,3-thiazolidine-2,4-dioneBDBM50131502-PUBCHEM54581270C24H21NO5Ssmall molecule--BINDINGDB-----------BTMVNTBNPIYHBM-QFIPXVFZSA-N
29084298251114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetEbdrup S (2003)126722311705256481RagaglitazarNN-622|(2S)-2-ETHOXY-3-{4-[2-(10H-PHENOXAZIN-10-YL)ETHOXY]PHENYL}PROPANOIC ACID|2-ETHOXY-3-[4-(2-PHENOXAZIN-10-YL-ETHOXY)-PHENYL]-PROPIONIC ACID(-) DRF 2725|Q27088511|DRF-2725|2-ETHOXY-3-[4-(2-PHENOXAZIN-10-YL-ETHOXY)-PHENYL]-PROPIONIC ACID|NNC-61-0029|(2S)-2-ETHOXY-3-[4-(2-PHENOXAZIN-10-YLETHOXY)PHENYL]PROPANOIC ACID|1NYX|DRF|(-)-DRF-2725|DRF2725|(S)-2-ETHOXY-3-[4-(2-PHENOXAZIN-10-YL-ETHOXY)-PHENYL]-PROPIONIC ACID|DB07675|RAGAGLITAZAR|GTPL2664|BDBM50109551-DRUGBANKDB07675C25H25NO5small molecule--BINDINGDB-----------WMUIIGVAWPWQAW-DEOSSOPVSA-N
29085298261114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetSantini C (2003)1265726322492197462-[3-Chloro-4-[3-[4-[(Z)-C-ethyl-N-hydroxycarbonimidoyl]-3-hydroxy-2-propylphenoxy]propylsulfanyl]phenyl]acetic acid3-CHLORO-4-[3-[2-PROPYL-3-HYDROXY-4-[1-(HYDROXYIMINO)PROPYL]PHENOXY]PROPYLTHIO]BENZENEACETIC ACID|BDBM50126019-PUBCHEM136088972C23H28ClNO5Ssmall molecule--BINDINGDB-----------JLVVAYSKHQLKES-PLRJNAJWSA-N
29086298271114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetSantini C (2003)126572632249219747Benzeneacetic acid, 3-chloro-4-((3-((3-phenyl-7-propyl-6-benzofuranyl)oxy)propyl)thio)-UNII-O937X0Z5EM|{3-CHLORO-4-[3-(3-PHENYL-7-PROPYL-BENZOFURAN-6-YLOXY)-PROPYLSULFANYL]-PHENYL}-ACETIC ACID|BENZENEACETIC ACID, 3-CHLORO-4-((3-((3-PHENYL-7-PROPYL-6-BENZOFURANYL)OXY)PROPYL)THIO)-|3-CHLORO-4-(3-(3-PHENYL-7-PROPYLBENZOFURAN-6-YLOXY)PROPYLTHIO)-PHENYLACETIC ACID|L-796,449|L796449|O937X0Z5EM|2-[3-CHLORO-4-[3-[(3-PHENYL-7-PROPYL-1-BENZOFURAN-6-YL)OXY]PROPYLSULFANYL]PHENYL]ACETIC ACID|L-796449|L 796449|Q27078434|{3-CHLORO-4-[3-(3-PHENYL-7-PROPYL-BENZOFURAN-6-YLOXY)-PROPYLSULFANYL]-PHENYL}-ACETIC ACID(L-796449)|GTPL2689|194608-80-5|BDBM50085040-PUBCHEM9891946C28H27ClO4Ssmall molecule--BINDINGDB-----------KAPDPGZDHUCILF-UHFFFAOYSA-N
29087298281114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetBrooks DA (2001)1140564222492297485-[[4-[2-(5-Methyl-2-phenyl-1,3-oxazol-4-yl)ethoxy]phenyl]methyl]-1,3-thiazolidine-2,4-dioneAD 5061|AD-5061|BM-131246|AD 7057|AD5061|5-{4-[2-(5-METHYL-2-PHENYL-4-OXAZOLYL)ETHOXY]BENZYL}-2,4-THIAZOLIDINEDIONE|GTPL2663|5-({4-[2-(5-METHYL-2-PHENYL-1,3-OXAZOL-4-YL)ETHOXY]PHENYL}METHYL)-1,3-THIAZOLIDINE-2,4-DIONE|Q27074311|HY-101758|AD-7057|CS-6704|5-[[4-[2-(5-METHYL-2-PHENYL-1,3-OXAZOL-4-YL)ETHOXY]PHENYL]METHYL]-1,3-THIAZOLIDINE-2,4-DIONE|AD7057|BDBM50064451-PUBCHEM9953271C22H20N2O4Ssmall molecule--BINDINGDB-----------GUTCYOKMCPFRGH-UHFFFAOYSA-N
29088298291114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetBrooks DA (2001)11405642224922404Rosiglitazone(RS)-5-{4-[2-(Methyl-2-pyridylamino)ethoxy]benzyl}-2,4-thiazolidinedion|Rosiglitazon|Rosiglitazonum|Rosiglitazone|()-5-[p-[2-(methyl-2-pyridylamino)ethoxy]benzyl]-2,4-thiazolidinedione|Rosiglitazona|BDBM50030474phl-rosiglitazone|avandaryl|avDRUGBANKDB00412C18H19N3O3Ssmall moleculeA10BD03|A10BG02|A10BD04122320-73-4BINDINGDB-----------YASAKCUCGLMORW-UHFFFAOYNA-N
29089298301099433741-KCNA5ATFB7|HCK1|HK2|HPCN1|KV1.5|PCN19606Homo sapiensunknowntargetCoghlan MJ (2001)113560992249239575N-[3-(4-Ethyl-benzenesulfonylamino)-2-hydroxy-indan-5-yl]-3-methoxy-benzamideN-((2R,3R)-3-(4-ETHYLPHENYLSULFONAMIDO)-2-HYDROXY-2,3-DIHYDRO-1H-INDEN-5-YL)-3-METHOXYBENZAMIDE|N-[3-(4-ETHYL-BENZENESULFONYLAMINO)-2-HYDROXY-INDAN-5-YL]-3-METHOXY-BENZAMIDE|BDBM50099581-PUBCHEM17748224C25H26N2O5Ssmall molecule--BINDINGDB-----------KCRNOVULDSNKBZ-DNQXCXABSA-N
29090298311099413738RP11-284N8.3KCNA3HGK5|HLK3|HPCN3|HUKIII|KV1.3|MK3|PCN39606Homo sapiensunknowntargetCoghlan MJ (2001)113560992249239749Methyl (1S,2S,3S,4R,5S,6S,8R,12S,15S,16S,22R,23R,24S)-3,4,24-triacetyloxy-22-[(1R)-1-acetyloxyethyl]-2,5,15-trimethyl-9-methylidene-19-oxo-23-prop-1-en-2-yloxy-7,20-dioxahexacyclo[13.9.0.02,12.05,11.06,8.016,22]tetracos-17-ene-6-carboxylate5-ISOPROPENYLOXY-1B,3A,10B-TRIMETHYL-2,3-DI(METHYLCARBONYLOXY)-5A-(1-METHYLCARBONYLOXYETHYL)-14-METHYLENE-1A-METHYLOXYCARBONYL-8-OXO-1A,1B,2,3,3A,3B,4,5,5A,6,8,10A,10B,11,12,12A,12B,13,14,14A-ICOSAHYDROOXIRENO[3'',2'':7,8]CHRYSENO[2,1-C]OXEPIN-4-YLACETA|BDBM50099583-PUBCHEM44290049C41H54O14small molecule--BINDINGDB-----------VBCYJMDXVYKTHI-SMYFPHPLSA-N
29091298321114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetHenke BR (1999)1061259422492497502-Phenyl-3-(4-methoxyphenethyl)-1H-indole-5-acetic acid{3-[2-(4-METHOXY-PHENYL)-ETHYL]-2-PHENYL-1H-INDOL-5-YL}-ACETIC ACID(GW 0207)|2-PHENYL-3-(4-METHOXYPHENETHYL)-1H-INDOLE-5-ACETIC ACID|258345-12-9|2-(3-(4-METHOXYPHENETHYL)-2-PHENYL-1H-INDOL-5-YL)ACETIC ACID|2-[3-[2-(4-METHOXYPHENYL)ETHYL]-2-PHENYL-1H-INDOL-5-YL]ACETIC ACID|{3-[2-(4-METHOXY-PHENYL)-ETHYL]-2-PHENYL-1H-INDOL-5-YL}-ACETIC ACID|GW0207|BDBM50083625-PUBCHEM10068664C25H23NO3small molecule--BINDINGDB-----------YZLHLVJLTOPOHC-UHFFFAOYSA-N
29092298331114645468-PPARGCIMT1|GLM1|NR1C3|PPARG1|PPARG2|PPARgamma9606Homo sapiensunknowntargetParks DJ (1998)9934490224925404Rosiglitazone(RS)-5-{4-[2-(Methyl-2-pyridylamino)ethoxy]benzyl}-2,4-thiazolidinedion|Rosiglitazon|Rosiglitazonum|Rosiglitazone|()-5-[p-[2-(methyl-2-pyridylamino)ethoxy]benzyl]-2,4-thiazolidinedione|Rosiglitazona|BDBM50030474phl-rosiglitazone|avandaryl|avDRUGBANKDB00412C18H19N3O3Ssmall moleculeA10BD03|A10BG02|A10BD04122320-73-4BINDINGDB-----------YASAKCUCGLMORW-UHFFFAOYNA-N